Temperature prediction transmitter

ABSTRACT

A system and method is provided for predicting a physical quality such as temperature, the measurement of which tends to be hindered by a time-related impediment. A single sensor is configured to detect, in real time, the physical quality Q detect , and one or more infinite impulse response filters are configured with time constants correlated to the time-related impediment. The infinite impulse filter(a) are configured to filter Q detect  to output a filtered quality measurement (Q filtered ). A processor is configured to calculate, in real time, the estimated or predicted quality Q estimate  using Q detect  and Q  filtered .

RELATED APPLICATION

This application claims the benefit of U.S. patent application Ser. No12/720355 entitled Temperature Prediction Transmitter, filed on Mar. 9,2010, the contents of which are incorporated herein by reference in itsentirety for all purposes.

BACKGROUND

1. Technical Field

This invention relates to the estimation of a signal with a physicaltime delay, and more particularly to a system of reducing orcompensating for the time delay caused by a physical impediment in asignal using an infinite impulse response (IIR) filter.

2. Background Information

Signals from sensors for a variety of physical phenomena (such aspressure, temperature, flow, acceleration, heat flux, and opticalintensity) may be delayed by a physical impediment. For example, inorder to measure the temperature of a process fluid flowing through aconduit, a temperature sensor may be positioned in the fluid flow.However, it is often necessary to physically separate the temperaturesensor from the fluid flow, e.g., due to compatibility issues. Forexample, the process fluid to be measured may be chemically incompatiblewith metallic temperature sensors, e.g., resulting in chemical attack orcontamination of the solution and/or electrodes. In addition, the fluidmay damage the temperature sensor, and build up of process fluid on thesensor may decrease the sensor's sensitivity. The fluid may also be partof a sanitary process, in which foreign objects such as sensors shouldnot contact the process fluid. These issues may thus tend to precludethe placement of conventional temperature detectors in direct contactwith the process fluid.

A conventional approach is to place the temperature sensor within aprotective casing, With such a casing, the temperature sensor may beplaced within the process fluid flow, while being protected from theprocess fluid by the casing. This approach relies on thermal conductionthrough the casing wall to the temperature sensor, to obtain temperaturedata. A drawback of this traditional solution is that the casing acts asa temperature insulator, thus impeding the sensor's ability to detecttemperature change.

In typical examples, casings for temperature detectors to be placed inconduits containing corrosive fluids are fabricated from polymers suchas PFA (perfluoroalkoxy polymer resin), PTFE (polytetrafluoroethylene),polyvinyl chloride (PVC), or various combinations thereof, such asperfluoroalkoxy-polytetrafluoroethylene co-polymer. The relatively poorthermal conductivity of these materials tends to adversely affect theaccuracy and response time provided by such external temperaturedetection approaches. Some techniques for compensating for theinaccuracy and delay of such temperature sensors involve the use ofadditional temperature sensors, including sensors positioned on theoutside of the conduit for the process fluid flow. Differences betweenthe signals captured from these multiple sensors may be used to helpestimate or otherwise compensate for the time delay. These techniques,however, may be impractical for many applications, such as thoseinvolving relatively complicated, expensive casings, such as those whichmay contain other devices in addition to sensors. It may thus be costprohibitive to use multiples of these relatively expensive, complicatedcasings on the conduit.

Referring to the chart of FIG. 1A, the temperature 23 detected by aconventional temperature sensor in a polymer casing is plotted relativeto actual process fluid temperature 21. As can be seen from the chart,there is a time lag between the process fluid temperature 21 and thedetection of the temperature 23 by the sensor. In addition, the detectedtemperature 23 has a relatively flattened amplitude and fails to reachthe highs and lows of the process temperature 21.

Turning to FIG. 1B, one attempt to overcome these drawbacks includespassing a signal 7, generated by the temperature sensor 3 within casing5, through a conventional filter 9. Conventional filter 9 is used toprocess the signal to reduce noise (e.g., electrical interference fromelectronic hardware), such as by using averaging techniques to filterout electronic noise and to output a conventionally estimatedtemperature 11.

As can be seen in FIG. 1C, this conventionally filtered signal 25, whileit may tend to reduce signal noise, tends not to compensate for the timelag. Rather, the conventionally filtered signal 25 may be viewed asincreasing the time lag.

A need therefore exists for a system that compensates for, or otherwisemitigates the effect of time-related impediments to accurate qualitymeasurements, without the need for multiple sensors.

SUMMARY

In an aspect of the invention, a system for predicting, in real time, aphysical quality with an impediment to accurate measurement, includes asensor configured to detect a physical quality (Q_(detect)), whereinmeasurement of the physical quality is subject to an impediment. Thesystem includes an infinite impulse response filter (IIR) configured tofilter Q_(detect) and to output a first filtered quality measurement(Q_(filtered1)) in real time. A processor is configured to calculate theestimated quality Q_(estimate) using Q_(detect) and Q_(filtered1).

In a variation of the foregoing aspect, the physical quality istemperature of a process fluid, as detected by a resistive temperaturedetector (RTD), with the physical impediment being a thermallyinsulative protective casing.

In another aspect of the invention, a method for transforming rawphysical quality data into an estimated measured quality, includesobtaining raw data representing a physical quality (Q_(detect)), inwhich an impediment exists to the detection of the physical quality. Themethod also includes filtering Q_(dectect) through an IIR, so that theIIR outputs Q_(filtered) ; and calculating, the a processor in realtime, the estimated measured quality (Q_(estimate)) using Q_(filtered1)and Q_(detect).

In variations of each of the foregoing aspects, multiple IIR filters maybe used to enhance output accuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features and advantages of this invention will bemore readily apparent from a reading of the following detaileddescription of various aspects of the invention taken in conjunctionwith the accompanying drawings, in which:

FIG. 1A is a chart of a model of prior art temperature detection ofprocess fluid flowing through a conduit;

FIG. 1B is a block diagram of prior art;

FIG. 1C is a chart of a model based on the prior art of FIG. 1B;

FIG. 2A is a block diagram of a system associated with an embodiment ofthe present invention;

FIG. 2B is a block diagram of a system associated with an embodiment ofthe present invention;

FIG. 3A is a block diagram of a system associated with an embodiment ofthe present invention;

FIG. 3B is a block diagram of a system associated with an embodiment ofthe present invention;

FIG. 4 is a flowchart of a method associated with an embodiment of theinvention;

FIG. 5 is a flowchart of a method associated with an embodiment of theinvention;

FIG. 6 is a flowchart of a method associated with an embodiment of theinvention;

FIG. 7 is a block diagram of a system associated with an embodiment ofthe present invention;

FIG. 8 is a chart of a computer modeled results associated with anembodiment of the invention; and

FIG. 9 is a chart of a computer modeled results associated with anotherembodiment of the invention.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings that form a part hereof, and in which is shown byway of illustration, specific embodiments in which the invention may bepracticed. These embodiments are described in sufficient detail toenable those skilled in the art to practice the invention, and it is tobe understood that other embodiments may be utilized. It is also to beunderstood that structural, procedural and system changes may be madewithout departing from the spirit and scope of the present invention.The following detailed description is, therefore, not to be taken in alimiting sense, and the scope of the present invention is defined by theappended claims and their equivalents. For clarity of exposition, likefeatures shown in the accompanying drawings shall be indicated with likereference numerals and similar features as shown in alternateembodiments in the drawings shall be indicated with similar referencenumerals.

Briefly, the inventor discovered that an otherwise conventional infiniteimpulse response (IIR) filter (e.g. “Kalman” or other low pass filters)may be configured to mimic, in real time, a physical system in which aphysical impediment (e.g., a time-related impediment) is responsible forunwanted time delays in a sensor's detection of a physical property. Asa specific example, the inventor discovered that such an HR filter maybe configured to mimic the effects that the aforementioned RTD (orthermister or thermocouple, etc.) casing would generate in delaying theprocess temperature from reaching the sensor. In particular, theinventor hypothesized that programming an IIR with a time constantcorrelated to that of the physical impediment would mimic this physicalimpediment. The inventor then discovered that this specially configuredHR filter may be used to effectively predict the temperature that wouldultimately reach the RTD, to thus substantially eliminate the time delayto provide enhanced, i.e., nearly instantaneous, real time temperaturedetection.

As alluded to above, using a filter in an attempt to reduce time delayis counterintuitive, since filters themselves tend to slow down andattenuate the actual transmission of a signal passing therethrough (see,e.g., FIG. 1C as discussed above). However, as will be discussedhereinbelow, the inventor surprisingly found that use of an HR filterconfigured with a time constant correlated to the physical impediment,could be used to effectively reduce or substantially eliminate the timedelay in the sensor's detection of the temperature. The inventor furtherfound that adding yet another filter may further enhance the quality ofthe processed data, i.e., by providing additional outputs for use in amathematical model capable of predicting a quality such as temperature.

These approaches thus capture multiple, sequential outputs from a singletemperature sensor, and effectively predict where the temperature ofthis single temperature sensor will ultimately settle, for improvedtemperature response times.

Optionally, a second infinite impulse filter may be used in conjunctionwith the first filter, with the difference between the two filters beingused to make further corrections. As will be discussed in greater detailbelow, the second filter may be a substantial duplicate of the firstfilter, but which in particular embodiments uses a time constant thatmay be greater than that used in the first filter. (The time constantsused may vary depending on the particular material e.g., casing, throughwhich the temperature must propagate.)

Functionally, the filters are similar to conventional RC circuits inwhich some part of a new measurement and some part of the previousreading are mixed together linearly (e.g., some fraction of the newmeasurement and the complementary fraction of the last reading). Theresponse is thus similar to the exponential response of an RC electricalcircuit, to effectively provide an exponential, or ‘infinite’ response,from a single sensor. An aspect of the invention is thus the realizationthat the response coming through the casing to the temperature sensorfrom a change in the measured temperature may be modeled substantiallyaccurately using this single or double-filtering approach. With thecorrect time constants, these embodiments enable one to effectively seehow much of the remaining (exponential) heat transfer hasn't yetarrived, and then optionally filter again with a longer time constant sothe difference is effectively corrected.

As used herein, the term “real time” refers to operations effectednearly simultaneously with actual events, such as to provide resultswhich are delayed nominally only by the execution speed of theprocessor(s) used.

Turning to FIG. 2A, an embodiment of the invention shown as system 100includes sensor 14, having a physical constraint (impediment) 12. Sensor14 is configured to detect a physical quality, Q_(detected) 16. An IIRfilter, IIR₁ 18, is configured to filter Q_(detected) 16 using aconstant k₁, and to output first filtered reading Q_(filtered1) 20.Constant τ₁ is predetermined to correlate to the known physicalimpediment 12. Processor 26 is configured to accept inputs Q_(detected)16 and Q_(filtered1) 20, and to use these two inputs to produceQ_(estimate) 28, e.g., using Equation 1 below.Q _(estimate)=2×Q _(detected) −Q _(filtered1)   Eq. 1

Although a single IIR filter may be used as shown, it should berecognized that additional HR filters may be used, to provide enhancedresults in many applications, as will be discussed below.

In particular examples, quality Q may be temperature and constant r maybe a time constant which correlates to a time delay associated with abarrier that is a relatively poor thermal conductor, as discussed belowwith respect to FIG. 2B. This embodiment may be particularly useful withtemperature sensors used in a corrosive process fluid. For example, aresistance temperature detector (“RTD”) may be encased in polypropyleneand inserted into relatively corrosive chemical process fluids. Whilethe polypropylene may protect the RTD from the process fluid, it hasrelatively low thermal conductivity, and therefore a relatively largetime constant (delay), e.g., which may be measured in minutes ratherthan seconds.

Referring now to the embodiment shown as system 102 of FIG. 2B, sensor14 is a temperature sensor 14, within a protective casing 12, whereinthe temperature sensor 14 is configured to detect T_(detected) 16, whichis the temperature inside the casing 12, In this embodiment, the IIRfilter, IIR₁ 18, is configured to filter T_(detected) 16 using a timeconstant τ₁, and to output first filtered temperature readingT_(filtered)1 20. Time constant τ₁ is set to approximately one half ofthe known time delay caused by the relatively low thermal conductivityof the casing 12. In the embodiment shown, processor 26 is configured toaccept inputs T_(detected) 16 and T_(filtered1) 20, and to use these twoinputs to produce T_(estimate) 28.

With reference now to FIGS. 3A & 3B, the inventor noted that in someapplications, combining the outputs of two (or more) IIR filters yieldedimproved results. (Specific experimental results are discussedhereinbelow in reference to FIGS. 7-9.) Such a multiple-filter system isshown at 200 in FIG. 3A, and is substantially similar to system 100, butfor the addition of a second IIR filter, IIR₂ 22 configured to receiveand process Q_(filtered1) 20, and to output Q_(filtered2) 24. IIR₂ 22 isthus configured to re-filter Q_(filtered1) 20 to provide a second input,Q_(filtered2) 24 , for processor 26. The first and second IIRs are eachprogrammed with time constants correlated to the physical impediment 12delaying the detection by sensor 14. In general, the time constant (τ₂)of the second IIR filter may be configured to be greater than orsubstantially equal to time constant (τ₁) of the first IIR filter. Inparticular exemplary embodiments shown and described herein, both IIRswere programmed with time constants of approximately one half that ofthe physical impediment 12.

Processor 26 is thus configured to receive both n 20, from IIR₁ 18, andQ_(filtered2) 24, from IIR₂ 22. Processor 26 is also configured toprocess these inputs to produce estimated temperature, Q_(estimate) 28.In particular embodiments, for example, the processor may be configuredto calculate Q_(estimate) 28 by the following Equation 2, i.e., bysubtracting the value of Q_(filtered2) 24 from twice the value ofQ_(filtered1) 20, or by Equation 3, both of which have been found toyield similar results in many applications.Q _(estimate)=(2×Q _(filtered1))−Q _(filtered2)   EQ. 2Q _(estimate) =Q _(filtered2)+(Q _(filtered2) −Q _(filtered1))   Eq. 3

Optionally, additional IIRs may be added, such as shown in phantom inFIG. 3A as IIR₃ 22′ , Such additional IIRs may be disposed in series orin parallel with any of the other IIRs. These additional IIRs may beused to either further refine an estimated quality, or to model anotherphysical impediment that may be present within the system such as in theevent an RTD easing is placed within another casing. For example, anadditional IIR 22′ may be placed in parallel with IIR 22, with bothreceiving either Q_(detected) or Q_(filtered1), to then feed theiroutputs Q_(filtered2) and Q_(filteredass), respectively, to processor26. The processor 26 may then use the following Equation 4 to calculateQestimate:Q _(estimate) =Q _(filtered1)+(Q _(filtered1) −Q _(filtered2))+(Q_(filtered1) −Q _(filteredadd)).   Eq. 4

As discussed above, any of the embodiments disclosed herein may beconfigured in which the physical quantity to be measured is temperature.Such a system is shown at 202 in FIG. 3B, which is substantially similarto system 200 (FIG. 3A), in which sensor 14 is a temperature sensor, thephysical impediment is the relatively poor thermal conductivity of acasing 12, and the time constants of the IIR filters IIR₁ 18, and IIR₂22 are correlated to the time constant of the casing.

In this embodiment, the second IIR filter, IIR₂ 22, is configured toreceive and re-filter T_(filtered1) 20, to output T_(filtered2) 24.Processor 26 is configured to receive both T_(filtered1) 20, from IIR₁18, and T_(filtered2) 24, from IIR₂ 22, and to generate estimatedtemperature, T_(estimate) 28. Thus, in this example, a raw signal from asingle temperature sensor is processed in series through both the firstand second IIR filters, creating an “in series” output, and is alsoprocessed separately through the first IIR filter, creating a “firstfilter” output. The “in series” output and the “first filter” output maybe combined to determine the estimated temperature.

As mentioned above, in particular embodiments, the processor 26 may beconfigured to combine the filtered outputs to produce T_(estimate) 28using the aforementioned Equation 1, 2, 3 and/or 4, in whichQ=temperature T.

As discussed above, the time constants are matched to the casingmaterial, e.g., they are set to one-half that of the casing inparticular embodiments. The time constant for a particular easing may bediscovered empirically, e.g., by sending process fluid of a knowntemperature through a conduit, and measuring the time required for atemperature sensor in the casing to reach the known fluid temperature.

The various embodiments of the subject invention may provide improvedspeed and accuracy, relative to conventional approaches by modeling theexpected delay to effectively predict where the measured quality (e.g.,temperature) will settle. Moreover, any of these embodiments may befurther configured to use Equation 5, discussed hereinbelow, to furtherreduce the time delay for enhanced, nominally real time output.

Embodiments of the claimed invention also involve methods for predictinga physical quality in applications involving a time-related impediment,such as predicting the temperature of a process fluid using atemperature sensor disposed within a casing. For convenience, thesemethods will be shown and described with respect to temperature measuredby a sensor disposed within an insulative casing or with any otherbarrier disposed between the sensor and the substance being measured. Itshould be recognized, however, that any one or more of the embodimentsshown and described herein may be used to analyze substantially anyquality for which speed of detection may be hindered by some physicalimpediment. Some non-exclusive examples of such qualities may includetemperature, pressure, flow, density, concentration, pH, ORP, index ofrefraction, turbidity, weight, mass, luminosity, position, etc.Moreover, it should be recognized that these qualities may be measuredwith substantially any type of sensor, including electronic, mechanical,electro-mechanical, chemical, and/or electro-chemical sensors, etc.

Turning now to FIG. 4, a method for transforming raw sensor datarepresenting a physical quality having a physical time constant (delay),into an estimated or predicted value, is shown as method 300. Thismethod includes 302, obtaining raw data representing temperature(T_(detected)) inside a casing within process fluid flow; 304, filteringT_(detected) through a first IIR (IIR₁), so that IIR1 outputsT_(filtered1); 306, optionally filtering T_(filtered1) through a secondIIR (IIR₂), so that IIR₂ outputs T_(filtered2); and 308, calculating theestimated temperature (T_(estimate)) using T_(filtered1) and optionally,T_(filtered2). This method may also be used with more than two IIRfilters, such as shown optionally at 310.

Turning now to FIG. 5, a method 400 is shown for modeling an estimatedtemperature of a process fluid flow. This method includes 402, encasinga temperature sensor within a casing; 404, inserting the casing in theprocess fluid flow; 406, reading the temperature inside the casing(T_(detected)) via the temperature sensor; 408, filtering T_(detected)through a first IIR (IIR₁), so that IIR₁ outputs a first filteredtemperature (T_(filtered1)). Method 400 optionally includes 410,filtering T_(filtered1) through a second IIR (IIR₂), so that IIR₂outputs a second filtered temperature (T_(filtered2)). At 414, theestimated temperature (T_(estimate)) is calculated using T_(filtered1)and optionally, T_(filtered2).

Method 500 of FIG. 6 is a method for estimating the temperature of aprocess fluid flow. This method includes 502, detecting the temperatureinside a casing (T_(detected)), the casing being inserted in a processfluid flow of a conduit; and 504, processing T_(detected) using atemperature estimation transmitter 506 (FIG. 7). As shown, transmitter506 may be an otherwise conventional process variable transmitter suchas commercially available from Invensys Systems, Inc. (Foxboro, Mass.),which includes the aforementioned IIR₁ 18, processor 26, and optionally,IIR₂ 22, as shown in phantom.

Turning to FIG. 8, the inventor tested embodiments of their inventionsuch as shown and described with respect to FIGS. 3A-3B, with computermodeling of a hypothetical process fluid. Temperature in degrees Celsius(y axis) is represented as a function of time in seconds (x axis). Theactual process temperature 30 is represented by the solid line. Thechart represents process fluid at 100° C. (e.g., boiling water) beingsent through a conduit, followed by process fluid of 0° C. (e.g., icewater) at approximately 71 seconds. The process temperature line 30thereby follows a step form. The chart also represents a gradual raisingand lowering of the temperature of the process fluid, so that processtemperature line 30 forms a sine wave.

In this example, the above-described T_(estimate) 28 more closely tracksthe solid process line 30. Although T_(estimate) 28 slightly lags theprocess 30, T_(estimate) 28 comes close to the amplitude of the actualprocess temperature. The chart indicates that T_(estimate) 28 reached100° C. at about 50 seconds, and fell to about 15° C. at about 95seconds. Since the process fluid 30 was rising in temperature at 95seconds, T_(estimate) 28 did not fall in temperature to the low of 0°Celsius.

This computer model also allowed the inventor to compare T_(estimate) 28to the temperature (T_(detected)) 16 detected by the temperature sensor,(represented in this FIG. 8 by dashed line 32). It may be seen that thanT_(estimate) 28 is appreciably better than T_(detected) line 32 atcapturing the full amplitude (high and low amplitude) of temperatureswings of process 30.

Turning now to FIG. 9, any of the foregoing embodiments may use anotheraspect of predicting the process temperature, which involves the slopeof the changes in temperature detected by the sensor. The inventorexperimented with simulations of process fluid in a conduit, with theprocess flow flowing past the casing. During experimentation with thecomputer models of FIGS. 4 and 5, using the configuration shown anddescribed with respect to FIGS. 3A, 3B, the inventor discovered that theslope of the sensor line 32 is proportional to the difference betweenthe sensor temperature readings, and the actual process temperature. Theinventor discovered that the following Equation 5 may be used to furtherenhance the estimated result, in which slope (Q_(estimatefinal))estimate 34 is determined by multiplying the slope of the sensor output(Q_(detect)) line 32 by a predetermined constant K, and adding theresult to the sensor line 32.Q _(estimatefinal)=(SlopeQ _(detect) ×K)+(Q _(detect))   Eq. 5As can be seen from the embodiment of FIG. 9, the slope estimate 34closely tracks the actual process fluid temperature 30, nominallywithout any delay, to effectively compensate for the physical impediment(e.g., time delay caused by an RTD casing, etc.) to provide nominallytrue, real time results. This embodiment thus effectively anticipateswhat temperature the sensor will detect before the temperature isactually detected. As also shown, nominally the full amplitude of theprocess fluid temperature is captured.

In this particular example, the value used for the constant K was 40. Itshould be recognized, however, that constant K is related to the thermaltime constant T discussed above. As such, the value of constant K isexpected to change based on the particular application, and may bedetermined by empirical testing as discussed hereinabove.

It may be seen that in this particular example, slope estimate 34,rather than forming a clear line, appears to be somewhat scatteredaround the process temperature 30. This may reflect noise which hasbecome part of the slope estimate. Therefore, processor 26 may befurther programmed with a conventional smoothing algorithm, e.g., whichaverages or uses standard deviations of the data to smooth out theestimate 34 for enhanced clarity.

Various embodiments of the present invention have been shown anddescribed herein with reference to use of an electronic sensor 14, suchas an RTD. It should be recognized, however, that substantially any typeof sensor, including mechanical (e.g., pneumatic), electro-mechanical,and/or electro-chemical sensors/control systems, may be used withoutdeparting from the scope of the present invention.

In the preceding specification, the invention has been described withreference to specific exemplary embodiments for the purposes ofillustration and description. It is not intended to be exhaustive or tolimit the invention to the precise form disclosed. Many modificationsand variations are possible in light of this disclosure. It is intendedthat the scope of the invention be limited not by this detaileddescription, but rather by the claims appended hereto.

Having described the invention, what is claimed is:
 1. A method fortransforming physical quality data into an estimated measured quality,comprising: a) obtaining, with a sensor in real time, data representinga physical quality (Q_(detect)), wherein an impediment exists to thedetection of the physical quality; b) filtering Q_(detect) through afirst IIR filter (IIR₁), wherein the IIR₁ outputs Q_(filtered1); c)calculating, with a processor in real time, the estimated measuredquality (Q_(estimate)) using Q_(filtered1) and Q_(detect) ; d) filteringQ_(filtered1) through another infinite impulse response filterconfigured to output another filtered quality measurement(Q_(filtered2)); and wherein said calculating (c) includes calculatingthe estimated quality Q_(estimate) using Q_(filtered1) andQ_(filtered2).
 2. The method of claim 1, wherein said obtaining (a)comprises obtaining, with a temperature sensor, data representing aphysical quality (Q_(detect) ) in the form of temperature, wherein theimpediment comprises a barrier disposed between the temperature sensorand the material; and said filtering (b) and calculating (c) is effectedby a temperature compensation transmitter.
 3. The method of claim 2,wherein the material comprises a process fluid and the barrier comprisesa casing disposed about the temperature sensor, wherein the casing isconfigured for extension into process fluid flow.
 4. The method of claim3, further comprising: e) disposing the temperature sensor within thecasing; and f) inserting the casing into the process fluid flow.
 5. Themethod of claim 1, wherein said calculating (c) comprises calculating,with the processor, Q_(estimate) by subtracting the value ofQ_(filtered2) from twice the value of Q_(filtered).
 6. The method ofclaim 1, wherein said calculating (c) comprises calculating, with theprocessor, Q_(estimate) by calculating the difference betweenQ_(filtered1) and Q_(filtered2), and adding the difference toQ_(filtered1).
 7. The method of claim 1, comprising configuring theinfinite impulse response filter to employ a first time constant (τ₁)correlated to the time-related impediment.
 8. The method of claim 7,comprising configuring the other infinite impulse response filter toemploy a second time constant (τ₂) correlated to the time-relatedimpediment.
 9. The method of claim 1, comprising: filteringQ_(filtered1) through an additional infinite impulse response filterconfigured to output an additional filtered quality measurement(Q_(filteredadd)); and wherein said calculating (c) includes calculatingthe estimated quality Q_(estimate) using Q_(filtered1), Q_(filtered2)and Q_(filteredadd).
 10. The method of claim 9, wherein said processoris configured to calculate the estimated quality Q_(estimate) using theformulaQ_(estimate)=Q_(filtered1)=Q_(filtered1)+(Q_(filtered1)−Q_(filtered2))+(Q_(filtered1)−Q_(filteredadd)).11. The method of claim 1, comprising recording, with the processor, aplurality of data points of Q_(detect) over time.
 12. The method ofclaim 11, comprising determining, with the processor, in real time, theslope of Q_(detect) at the plurality of data points.
 13. The method ofclaim 12, wherein said calculating (c) comprises determiningQ_(estimate) using the slope of Q_(detect) detected at the plurality ofdata points.
 14. The method of claim 13, wherein said calculating (c)comprises calculating with the processor in real time, a final value forQ_(estimate), denoted as Q_(estimatefinal), by the formulaQ_(estimatefinal)=Slope Q_(detect)×K)+(Q_(estimate)) wherein K is aconstant having a value correlated to the time-related impediment.